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ETHSofia

Project Details

This project is part of our ETHSofia initiative, where we achieved remarkable success. Our project earned three first-place bounties from Chainbase, iExec, and SeeBlocks, as well as a third-place bounty in the AI Open Track competition at the ETHSofia hackathon.

Below, you will find the demo video, presentation, and all other resources needed to explore the project:
Demo Video, Presentation, and Resources: https://dorahacks.io/buidl/17725

Project Setup Guide

Welcome to our project! This guide will walk you through the steps required to set up and run the project locally.

Prerequisites

Make sure you have the following installed on your machine:

  • Node.js (for running the frontend and backend)
  • npm (Node package manager)
  • Python (for running the model/server)

Setup Instructions

Follow these steps to get the project up and running:

1. Clone the Repository

Start by cloning the repository to your local machine:

git clone <repository-url>
cd <repository-folder>

2. Set Up the Frontend

Navigate to the frontend folder and install the necessary dependencies:

cd frontend
npm install

Additionally, install react-hot-toast to manage notifications:

npm install react-hot-toast

Once the dependencies are installed, you can start the frontend development server:

npm run dev

The frontend should now be running.

3. Start the Python Model/Server

Open a new terminal and navigate to the root of the project directory. Run the Python server:

python model/server.py

This will start the server handling the machine learning model or other backend logic.

4. Set Up the Backend

In a new terminal, go to the backend folder and install the necessary dependencies:

cd backend
npm install

After that, navigate to the src folder and start the backend server:

cd src
node server.js

And that's it! 🎉

Your project should now be fully set up with the frontend, backend, and Python model running.

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We enable private, AI-driven marketing by grouping anonymous users for targeted campaigns. Companies reach audiences without personal data, and users earn revenue while maintaining full privacy.

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